Project Summary: A fundamental mammalian behavior is the ability to successfully navigate through our environment to reach a goal (e.g. a left turn decision towards your favorite restaurant). What seems like a simple behavior is the result of complex brain computations like the representation of space, decision-making and memory. The Hippocampus (Hipp) and the medial entorhinal cortex (MEC) are critical brain regions for memory and the representation of our environment. Hipp neurons are active in specific locations in an environment, exhibit context dependent activity, and can code for elapsed time. MEC neural activity has been mainly studied during open-field foraging behavior and shown to represent spatial and navigational variables like position, head- direction, and speed. Contrary to the Hipp, the role of MEC in more complex behavior, such as goal-directed navigation, is unknown. We hypothesize that MEC neurons are part of the circuitry critical for decision-making during goal-directed navigation. This hypothesis is tested through a series of goal-directed spatial decision making tasks while recording MEC neurons in rodents. First, we predict that MEC neurons represent behaviorally relevant task features during a cue-based spatial decision making task. We designed a task in which rats make spatial decisions (go left, go right) towards a food reward based on a visually presented cue. The spiking activity of MEC neurons is recorded and related to the animal's behavior and features of the environment (e.g., cue, rewards, animal's position). In our preliminary data we demonstrate that animals can learn the task, recorded isolated cells with spatial and task-related coding. Second, we predict that MEC population activity represents decision related information. A decision delay is introduced to test this hypothesis, in which the animal needs to remember the cue before making the spatial decision. We expect to accurately predict the upcoming decision through neural population decoding analyses of the activity during the delay period. Our preliminary results demonstrate that animals can perform this complex task. Third, we predict that Hipp/MEC dynamically interact in service of spatial decisions. We use minimally invasive multichannel probes simultaneously recording Hipp/MEC through task learning, and predict that hippocampal events (sharp-wave ripples) will reinstate neural population patterns in the MEC related to the upcoming spatial decision. Further, we predict that Hipp/MEC interactions are indicative of behavioral performance through learning. In our preliminary data we demonstrate the use of these probes, and the stability of recordings over 7 weeks. Through a combination of novel behavioral and electrophysiological techniques, this project will elucidate the role of MEC in spatial-decisions. Furthermore, understanding how MEC and Hipp support these complex cognitive behaviors would fundamentally influence models of brain function in the healthy, mentally ill, and diseased brain, potentially leading to prevention and cure.